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胸径是评价林木生长状况的重要参数之一。针对接触式人工测量自动化程度低和基于点云的现有算法提取树木胸径精度不高的问题,提出一种基于点云数据的自动准确获取树木胸径的新方法。该方法以树木点云数据为基础,运用蚁群算法和B样条曲线拟合技术,实现树木胸径的自动准确提取。对实验区树木测量计算,结果表明,利用该方法提取树木胸径的均方根误差为±0.19 cm,平均绝对误差为0.15 cm,相对于基于点云的传统算法提取精度分别提高了50%和60.7%。该方法基于高精度点云数据,实现了树木胸径的无损自动提取,在精准林业领域具有推广价值。
DBH is one of the important parameters to evaluate the growth status of trees. In order to solve the problem of low precision of manual measurement of contact and low accuracy of extracting DBH from existing algorithms based on point cloud, a new method of automatic accurate retrieval of DBH based on point cloud data is proposed. Based on the point cloud data of trees, this method uses ant colony algorithm and B-spline curve fitting technique to realize automatic and accurate extraction of DBH. The results show that the root mean square error (RMSE) of DBH extracted by this method is ± 0.19 cm and the average absolute error is 0.15 cm, which is improved by 50% and 60.7% respectively compared with the traditional algorithm based on point cloud %. Based on the high-precision point cloud data, this method realizes the non-destructive automatic extraction of DBH and has the promotion value in the precision forestry field.